NAME

       cnvkit_segmetrics - Compute segment-level metrics from bin-level log2 ratios.

DESCRIPTION

       usage: cnvkit.py segmetrics [-h] -s SEGMENTS [--drop-low-coverage]

       [-o FILENAME] [--mean] [--median] [--mode]
              [--t-test]  [--stdev]  [--sem]  [--mad] [--mse] [--iqr] [--bivar] [--ci] [--pi] [-a
              ALPHA] [-b BOOTSTRAP] [--smooth-bootstrap] cnarray

   positional arguments:
       cnarray
              Bin-level copy ratio data file (*.cnn, *.cnr).

   options:
       -h, --help
              show this help message and exit

       -s SEGMENTS, --segments SEGMENTS
              Segmentation data file (*.cns, output of the 'segment' command).

       --drop-low-coverage
              Drop  very-low-coverage  bins  before  calculations  to  avoid  negative  bias   in
              poor-quality tumor samples.

       -o FILENAME, --output FILENAME
              Output table file name.

   Statistics available:
       --mean Mean log2 ratio (unweighted).

       --median
              Median.

       --mode Mode (i.e. peak density of bin log2 ratios).

       --t-test
              One-sample t-test of bin log2 ratios versus 0.0.

       --stdev
              Standard deviation.

       --sem  Standard error of the mean.

       --mad  Median absolute deviation (standardized).

       --mse  Mean squared error.

       --iqr  Inter-quartile range.

       --bivar
              Tukey's biweight midvariance.

       --ci   Confidence interval (by bootstrap).

       --pi   Prediction interval.

       -a ALPHA, --alpha ALPHA
              Level  to  estimate  confidence  and  prediction intervals; use with --ci and --pi.
              [Default: 0.05]

       -b BOOTSTRAP, --bootstrap BOOTSTRAP
              Number of bootstrap iterations to estimate  confidence  interval;  use  with  --ci.
              [Default: 100]

       --smooth-bootstrap
              Apply  Gaussian noise to bootstrap samples, a.k.a.  smoothed bootstrap, to estimate
              confidence interval; use with --ci.